A Framework for Fusing Video and Wearable Sensing Data by Deep Learning

Ting Hui Chiang, Po Yi Kuo, Huan Ruei Shiu, Yu Chee Tseng

研究成果: Conference contribution同行評審

摘要

Both cameras and IoT devices have their particular capabilities in tracking human behaviors and statuses. Their correlations are, however, unclear. In this work, we propose a framework for integrating video and wearable sensing data for smart surveillance, such as person identification and tracking. Using biometric features such as fingerprint, iris, gait, and face may lead to good recognition results. However, these approaches all have their limitations in distance and privacy concerns. In this work, we present a data fusion framework based on deep learning for fusing the aforementioned data. Here, using deep learning is to help adaptively learn the hidden bindings of these data. We demonstrate how to retrieve data of interest from IoT devices, which are attached on human objects, and correctly tag them on the human objects captured by a camera, thus correlating video and IoT data. Potential applications of this framework include smart surveillance and friendly visualization. We then show a case study, including integrating video data with body movement and physiological data.

原文English
主出版物標題Proceedings of the 2022 8th International Conference on Applied System Innovation, ICASI 2022
編輯Shoou-Jinn Chang, Sheng-Joue Young, Artde Donald Kin-Tak Lam, Liang-Wen Ji, Stephen D. Prior
發行者Institute of Electrical and Electronics Engineers Inc.
頁面134-139
頁數6
ISBN(電子)9781665496506
DOIs
出版狀態Published - 2022
事件8th International Conference on Applied System Innovation, ICASI 2022 - Nantou, Taiwan
持續時間: 21 4月 202223 4月 2022

出版系列

名字Proceedings of the 2022 8th International Conference on Applied System Innovation, ICASI 2022

Conference

Conference8th International Conference on Applied System Innovation, ICASI 2022
國家/地區Taiwan
城市Nantou
期間21/04/2223/04/22

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